Earth surface processes and environmental sustainability in China: preface

Fu, Bojie; Zhu, Yan; Wang, Shuai

doi:10.1017/s1755691018000683

Cited by 1 publication

(1 citation statement)

References 4 publications

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“…China is one of the fast-growth emerging nations in the world [2], achieving its higher record of gross domestic product (GDP) development of 9.6% in the last 20 years [15,16]. However, this relative fast growth was made at the expense of the ES depletion and high environmental damage [17][18][19]. With increasing negative environmental externality that affected the wellbeing and the public health of their local citizens [15], the Chinese government decided to embrace an ambitious plane of sustainable development that required changes in key sectors such as agriculture, energy and industry [6,15,16,20,21].…”

Section: Introductionmentioning

confidence: 99%

Using Satellite Image Fusion to Evaluate the Impact of Land Use Changes on Ecosystem Services and Their Economic Values

Wang¹,

Padmanaban

Mbanze

et al. 2021

Remote Sensing

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Accelerated land use change is a current challenge for environmental management worldwide. Given the urgent need to incorporate economic and ecological goals in landscape planning, cost-effective conservation strategies are required. In this study, we validated the benefit of fusing imagery from multiple sensors to assess the impact of landscape changes on ecosystem services (ES) and their economic values in the Long County, Shaanxi Province, China. We applied several landscape metrics to assess the local spatial configuration over 15 years (2004–2019) from fused imageries. Using Landsat-7 Enhanced Thematic Mapper Plus (ETM+), Landsat-8 Operational Land Imager (OLI) and Indian Remote Sensing Satellite System Linear Imaging Self Scanning Sensor 3 (IRS LISS 3) imageries fused for 2004, 2009, 2014 and 2019, we reclassified land use/land cover (LULC) changes, through the rotation forest (RF) machine-learning algorithm. We proposed an equivalent monetary metric for estimating the ES values, which also could be used in the whole China. Results showed that agriculture farmland and unused land decreased their spatial distribution over time, with an observed increase on woodland, grassland, water bodies and built-up area. Our findings suggested that the patterns of landscape uniformity and connectivity improved, while the distribution of landscape types stabilized, while the landscape diversity had a slight improvement. The overall ES values increased (4.34%) under a benefit transfer approach, mainly concerning woodland and grassland. A sensitivity analysis showed the selected economic value (EV) was relevant and suitable for the study area associated with our ES for LULC changes. We suggested that changes in landscape patterns affected the ESV trends, while the increases on some LULC classes slightly improved the landscape diversity. Using an interdisciplinary approach, we recommend that local authorities and environmental practitioners should balance the economic benefits and ecological gains in different landscapes to achieve a sustainable development from local to regional scales.

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